Flow field chromatography reconstruction method, system and equipment, storage medium and program product

Abstract

The invention relates to the technical field of optical tomography, and provides a flow field tomography reconstruction method, system and device, a storage medium and a program product, and the method comprises the steps: building a double-line joint solving equation, and combining the two-line joint solving equation into a single optimization equation; introducing a mixed regularization constraint into a single optimization equation, and establishing a mixed regularization double-line joint solution calculation mathematical model; based on a mixed regularization double-line joint solution calculation mathematical model, setting an absorption coefficient non-negative criterion, and introducing temperature prior information of a flow field to obtain a mixed regularization solution mathematical model with temperature limit prior constraints; and solving the mixed regularization solving mathematical model with the temperature limit priori constraint to obtain an absorption coefficient, and calculating the temperature distribution of the flow field by using the absorption coefficient. By means of the method, regularization constraint can be carried out on the flow field temperature reconstruction result, meanwhile, strong constraint is carried out on calculation solution by introducing multiple kinds of physical prior information, and the flow field chromatography reconstruction precision is remarkably improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of optical tomography, and in particular relates to a flow field tomography reconstruction method, system, device, storage medium and program product. Background Art

[0002] Linear tomography combined with the two-line thermometry method is widely used in the reconstruction of temperature and concentration in various combustion fields. When the temperature distribution is reconstructed by the two-line method, the concentration distribution can be quantitatively calculated by the absorption coefficient distribution and Beer-Lambert of one of the absorption lines. However, in the linear two-line tomography method, the absorption coefficient distributions of the two absorption lines are calculated independently, making the temperature reconstruction extremely sensitive to experimental noise and tomography calculation errors, showing non-physical artifacts or local distortions in the tomography reconstruction results. The above problems will become more serious in the case of insufficient projection information or sparse projections. In addition, the noise resistance and temperature sensitivity range of the selected spectral line pair will also directly affect the reconstruction results.

[0003] Joint solution of the two lines and introduction of ratio constraints is a possible idea to improve the reconstruction accuracy of the two-line tomography method. Summary of the Invention

[0004] To solve the above problems, the present invention provides a flow field tomography reconstruction method, system, device, storage medium and program product, which jointly and synchronously solve the absorption coefficients of two absorption lines, and introduce hybrid regularization for the absorption coefficient distribution and the absorption coefficient ratio distribution respectively to suppress the random fluctuations of each result.

[0005] The present invention can be implemented by the following solutions: In a first aspect, an embodiment of the present invention provides a flow field tomography reconstruction method, including: Select two absorption lines, jointly solve the absorption coefficients of the two absorption lines, establish a two-line joint solution equation and combine it into a single optimization equation; Introduce hybrid regularization constraints into the single optimization equation to establish a hybrid regularization two-line joint solution calculation mathematical model; Based on the hybrid regularization two-line joint solution calculation mathematical model, set the non-negativity criterion of the absorption coefficient, and introduce the prior information of the temperature of the flow field to obtain a hybrid regularization solution mathematical model with prior constraints of temperature bounds; Solve the hybrid regularization solution mathematical model with prior constraints of temperature bounds to obtain the absorption coefficient, and calculate the temperature distribution of the flow field using the absorption coefficient.

[0006] As a preferred means, The two absorption lines are the center frequencies of the near-infrared bands of water molecules in the main combustion products of hydrocarbon fuels, which are 7185.597 cm -1 and 7444.352 cm-1 Absorption spectral lines.

[0007] As a preferred means, Hybrid regularization is to use Tikhonov Regularization and TV Regularization methods in combination.

[0008] As a preferred means, The dual-line joint solution computational mathematical model of hybrid regularization includes three parts: the first part is the computational fidelity term, the second part is the hybrid regularization term for each absorption line, and the third part is the hybrid regularization term for the absorption coefficient ratio distribution.

[0009] As a preferred means, The dual-line joint solution computational mathematical model of hybrid regularization selects empirical regularization weight parameters to balance the importance of each sample.

[0010] As a preferred means, Using the absorption coefficient to calculate the temperature distribution of the flow field, including: Discretize the target reconstruction region into multiple grid cells, and regard the thermophysical parameters in each grid cell as uniformly distributed; Calculate the temperature value of each grid cell according to the ratio of the absorption coefficients of two absorption lines; Integrate the temperature values of all grid cells to obtain the temperature distribution of the flow field.

[0011] In a second aspect, based on the same inventive concept, an embodiment of the present invention further provides a flow field tomography reconstruction system, which includes an absorption coefficient joint solution module, a hybrid regularization module, a prior constraint module, and a solution calculation module; The absorption coefficient joint solution module is used for: selecting two absorption lines, jointly solving the absorption coefficients of the two absorption lines, establishing a dual-line joint solution equation and merging it into a single optimization equation; The hybrid regularization module is used for: introducing hybrid regularization constraints into the single optimization equation to establish a dual-line joint solution computational mathematical model of hybrid regularization; The prior constraint module is used for: based on the dual-line joint solution computational mathematical model of hybrid regularization, setting the non-negativity criterion of the absorption coefficient, and introducing the temperature prior information of the flow field to obtain a hybrid regularization solution mathematical model with temperature boundary prior constraints; The solution calculation module is used for: solving the hybrid regularization solution mathematical model with temperature boundary prior constraints to obtain the absorption coefficient, and using the absorption coefficient to calculate the temperature distribution of the flow field.

[0012] In a third aspect, based on the same inventive concept, an embodiment of the present invention further provides an electronic device, including at least one processor and at least one memory that are electrically connected; The memory is electrically connected to the processor, wherein the memory stores instructions executable by at least one of the processors, and the instructions are executed by at least one of the processors to enable at least one of the processors to execute any of the foregoing flow field tomography reconstruction methods.

[0013] In a fourth aspect, based on the same inventive concept, an embodiment of the present invention further provides a computer storage medium, in which a computer program is stored; When the computer program is executed by a processor, it implements any of the foregoing flow field tomography reconstruction methods.

[0014] In a fifth aspect, based on the same inventive concept, an embodiment of the present invention further provides a computer program product, which is stored in at least one storage medium; The computer program product includes several instructions for enabling at least one electronic device to execute any of the foregoing flow field tomography reconstruction methods.

[0015] Compared with the prior art, the present invention has the following advantages: 1. Dual-line joint solution solves the drawback that traditional independent solutions cannot establish connections. At the same time, adding a ratio can indirectly control the temperature field; 2. Introduce a penalty method of hybrid regularization to cope with flow fields of various complex configurations; 3. In the calculation process, in addition to adding the non-negativity criterion of the absorption coefficient, physical information of temperature boundaries is also added to strongly constrain the solution result and improve the reconstruction accuracy.

[0016] Other features and advantages of the present invention will be described in the following specification, and some of them will be obvious from the specification, or can be understood by implementing the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures pointed out in the specification, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 The flowchart of a flow field tomography reconstruction method according to an embodiment of the present invention is shown; Figure 2 Shows the curve of the spectral line intensity and its ratio of the absorption lines selected in the embodiments of the present invention varying with temperature; Figure 3 Shows the simulation results of tomographic reconstruction of the combustion field models of three configurations using different calculation methods according to the embodiments of the present invention; Figure 4 Shows that under different numbers of projection angles Figure 3 The image errors of tomographic reconstruction simulations of three combustion field models using different calculation methods respectively: (a) is the Gaussian configuration, (b) is the "top-hat" configuration, and (c) is the mixed configuration; Figure 5 Shows Figure 3 The temperature reconstruction results of experimental tests on the Mckenna combustion flame by three combustion field models: (a) is the reconstruction result of the present invention, (b) is the ART reconstruction result, and (c) is the Tikhonov reconstruction result; Figure 6 Shows Figure 3 The comparison between the thermocouple measurement data and the experimental tomographic results of three combustion field models; Figure 7 Shows a schematic structural diagram of an electronic device according to an embodiment of the present invention. Detailed implementation manners

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0020] The flow field tomographic reconstruction method of the present invention is applicable to different temperature-measuring absorption line pairs of different components. The two absorption spectral lines should have significantly different low-state energy levels and strong spectral line intensities within the temperature range of the flow field to be measured.

[0021] For the convenience of description, a specific case of a double line is given as follows: Selecting the water molecule, the main combustion product of hydrocarbon fuel, as the target, the temperature-measuring absorption lines (absorption spectral lines) are the spectral line pair of 7185.597 cm -1 and 7444.352 cm -1 (7185.597 cm -1 and 7444.352 cm -1 are the spectral line center frequencies and are in the near-infrared band), which have sufficient temperature-measuring sensitivity within the temperature range of the hydrocarbon fuel combustion flow field.

[0022] Figure 1 The flow field diagram of a flow field tomography reconstruction method according to an embodiment of the present invention is shown.

[0023] Let the absorption coefficients of the two selected absorption lines be α ν1 , α ν2 , respectively. The least-squares solutions of the following equations can be obtained by Tikhonov Regularization: , where: μR ( α ν ) is the regularization term that controls the smoothness; W is the projection weight matrix, and its elements are the path lengths when the laser passes through a specific grid. When the optical path arrangement is determined, W the matrix can be calculated through algebraic geometric relationships; A is the integrated absorbance, which can be obtained by non-linearly fitting the experimental spectrum with the Voigt function of the spectrum.

[0024] When a laser beam with a frequency of v [cm -1 passes through the target area, due to the absorption effect of water molecules, its intensity attenuates along the optical path L [cm]. This process can be quantitatively described by the Beer-Lambert law as the integrated absorbance A ν,i [cm -1 , which can be expressed as the following formula: , where: I 0 is the incident light intensity; I t is the transmitted light intensity; i represents the i th optical path; j represents the j th grid; α ν,j [cm -2 = P j X j S ( T j ) is the absorption coefficient at a frequency of v [cm -1 ; P [atm] is the local pressure; X is the mole fraction of the absorbing gas;S ( T ) [cm -2 atm -1 is the temperature-dependent spectral line intensity.

[0025] The absorption coefficient is detailed below α ν1 、 α ν2 's solution process: In the dual-line combined solution method, the system of equations is combined into a single optimization equation to jointly calculate the distribution of the dual-line absorption coefficient when the error between the dual-line integral value and the measured value is minimized. The combined single optimization equation is: , where the regularization term with α ν1 , α ν2 two variables R ( α ν1 , α ν2 ) can ensure obtaining a reliable computational solution for this single optimization equation and can suppress the fluctuations in dual-line temperature measurement.

[0026] Tikhonov Regularization and Total-variation Regularization (TV Regularization / TV regularization / total variation regularization) are two classical regularization methods. Among them, Tikhonov Regularization is suitable for image processing with smooth distributions and not suitable for scenarios with sharp gradient boundaries. TV Regularization has advantages in removing image noise and preserving image edges.

[0027] For the above single optimization equation, in this embodiment, by mixing the Tikhonov Regularization and TV Regularization methods, a mixed regularization constraint is imposed on the dual-line ratio distribution and each absorption coefficient distribution, and the following mixed-regularization dual-line combined solution computational mathematical model is established: , where: is the regularization weight parameter.

[0028] The above hybrid regularized dual-line joint solution calculation mathematical model can suppress image noise while ensuring the true gradient boundary of the image. The first row (first part) of the model is the calculation fidelity term, the second row (second part) is the hybrid regularization term for each absorption line, and the third row (third part) is the hybrid regularization term for the absorption coefficient ratio distribution. Among them, the second row (second part) ensures the accuracy of each absorption coefficient distribution solution, which is helpful for the subsequent concentration distribution calculation, and the third row (third part) determines the distribution characteristics of the dual-line ratio, which directly controls the final temperature distribution.

[0029] The hybrid regularized two-line joint solution calculation mathematical model requires the selection of appropriate regularization weight parameters to balance the contribution of each part.

[0030] In this embodiment, by solving multiple representative typical cases of flow field distribution in advance, regularization weight parameters with higher reconstruction accuracy are empirically determined. In the case of no noise and 2% noise level, this embodiment provides a set of reliable empirical regularization weight parameters, as shown in Table 1.

[0031] Table 1

[0032] Where: e represents the power of 10.

[0033] It should be pointed out that cross validation is also a feasible method for selecting regularization weight parameters, but its computational complexity is large. In addition, the selection of regularization weight parameters can also be assisted by artificial intelligence methods such as machine learning. The reference regularization parameters provided in Table 1 are applicable to the water molecule line pairs used in this embodiment, and other line selection methods can be optimized according to any of the aforementioned feasible methods.

[0034] In addition, the physical prior information of the combustion flow field can be used to constrain the computational solution. For example, for the traditional computational method, the set of equations , the non-negative criterion of the absorption coefficient can be set for constraint solving.

[0035] Specifically, in addition to the non-negative criterion of the absorption coefficient, this embodiment also introduces temperature prior information of the flow field for constraint.

[0036] Figure 2 The absorption line 7185.597 cm selected in this example is plotted -1 and 7444.352 cm -1 The curve of spectral line intensity and double line ratio changing with temperature.

[0037] from Figure 2As can be seen, the ratio of the selected absorption line pairs shows a monotonically increasing trend with the increase of temperature in the range of 273 K to 2000 K. Therefore, when the prior information of the upper and lower limits of the flow field temperature can be obtained, the dual-line ratio R can be used to further constrain the above-mentioned dual-line joint solution calculation mathematical model of hybrid regularization by setting the temperature limit.

[0038] The hybrid regularization solution mathematical model with prior constraints of temperature limit is as follows: , It should be noted that the temperature limits of the combustion flow field can be obtained through other optical measurement methods, computational fluid dynamics simulation (CFD), or thermocouple measurement.

[0039] Solve the hybrid regularization solution mathematical model with prior constraints of temperature limit to obtain the optimal solution, that is, the absorption coefficient α ν1 , α ν2 .

[0040] When the absorption coefficients of the two absorption lines α ν1 , α ν2 are calculated, the local temperature R j of the combustion flow field can be deduced from the ratio of the absorption coefficients, which can be expressed by the following formula: , In the formula: h [J∙s] is the Planck constant; c [cm∙s -1 is the speed of light; k [J∙K -1 is the Boltzmann constant; E " [cm -1 is the low energy level of the spectral line; T 0[K] is the reference temperature.

[0041] By transforming the above local temperature formula, the calculation expression of temperature T j can be obtained: , Solve the calculation expression of temperature T j , and the temperature distribution of the flow field can be obtained.

[0042] According to this embodiment, it is possible to perform regularization constraints on the reconstructed results of the flow field temperature, and strongly constrain the calculation and solution by introducing a variety of physical prior information, which can significantly improve the tomography reconstruction accuracy and provide a new calculation method for the dual-line temperature measurement tomography technology.

[0043] Control example First, a simulation test is carried out by using a hybrid regularization-based dual-line joint solution combustion flow field tomography reconstruction method proposed by the present invention, and it is compared with traditional reconstruction algorithms. The traditional algorithms used include ART (Algebra Reconstruction Technique) and Tikhonov Regularization.

[0044] The flow field models used for testing include three types: Gaussian configuration, "top hat" configuration, and hybrid configuration. Among them, the flow field temperature and the flow field water molecule concentration adopt the same configuration. The temperature distribution range is from 400 K to 1800 K, and the water molecule concentration range is from 0.01 to 0.15. The target reconstruction area is discretized into 20 × 20 grid cells, and the grid resolution is 1 cm. Four projection angles are adopted, and 20 equally spaced light beams are set at each angle. The specific simulation process includes the following steps: Step 1, simulate the absorbance in each grid of the simulation flow field model through the HITRAN database.

[0045] Step 2, calculate the absorption spectra of all light beams passing through the target area according to the element sizes in the absorption weight matrix W determined by the optical path layout.

[0046] Step 3, fit the simulated absorption spectra using the Voigt spectral model to obtain the integrated absorbance of the target absorption line.

[0047] Step 4, substitute the integrated absorbance vectors of the two absorption lines obtained by fitting in Step 3 into the aforementioned "hybrid regularization solution mathematical model with temperature boundary prior constraints" for optimization and solution. It should be noted that only the non-negative criterion constraint of the absorption coefficient is added during the simulation calculation process.

[0048] Step 5, combine the absorption coefficient distributions of the two absorption lines calculated, and calculate the temperature distribution in combination with the aforementioned " T j calculation expression of temperature".

[0049] Under the above simulation reconstruction and simulation steps, the reconstruction simulation of the combustion flow field with three configurations is completed, and the reconstruction results are as Figure 3As shown, it can be seen that the reconstruction performance of a combustion flow field tomography reconstruction method with hybrid regularization and dual-line joint solution proposed by the present invention is significantly better than other methods, effectively suppressing reconstruction artifacts and improving the reconstruction accuracy in high-temperature regions.

[0050] To quantitatively evaluate the accuracy levels of various methods at different numbers of projection angles, the image errors of each reconstruction result were calculated, as Figure 4 shown. The reconstruction errors of all methods show a downward trend as the number of projection angles increases. Among them, the two reconstruction methods of ART and Tikhonov Regularization have similar accuracy levels, while the combustion flow field tomography reconstruction method with hybrid regularization and dual-line joint solution proposed by the present invention significantly reduces the reconstruction error. After the number of projector angles reaches 4, the reconstruction error is lower than 2.5%, and even within 1%. This accuracy level is also much higher than the calculation results in similar literature.

[0051] Verification example To verify that the combustion flow field tomography reconstruction method with hybrid regularization and dual-line joint solution proposed by the present invention also has an improvement effect in practical applications. This embodiment is further illustrated by experimental measurement.

[0052] The experimental measurement object is a planar flame generated by a standard Mckenna burner, and the measurement height is 5 mm above the burner. The experiment uses 4 projection angles, with 25 equally spaced light beams arranged at each angle and a resolution of 4 mm. The flame fuel is a CH4 / air premixed gas, where the methane flow rate is set to 1.31 L / min and the air flow rate is set to 15.6 L / min. The equivalence ratio can be calculated as 0.8. To stabilize the flame, the flow rate of the accompanying nitrogen protective gas is set to 20 L / min. Two lasers with central wavelengths of 1392 nm and 1343 nm are used to obtain two absorption lines of water molecules at 7185.597 cm -1 and 7444.352 cm -1 by time-division multiplexing.

[0053] The experimental absorption spectrum is obtained by detecting the laser light intensity and baseline fitting. Then, according to steps 3 to 5 in the control example, the experimental data is processed, and finally the two-dimensional temperature distribution 5 mm above the Mckenna burner is reconstructed. The experimental reconstruction result is as Figure 5 shown.

[0054] The experimental results show that the combustion flow field tomography reconstruction method with hybrid regularization and dual-line joint solution proposed by the present invention can also effectively suppress reconstruction artifacts and restore the flat characteristics of the central region of the Mckenna combustion flame to the greatest extent during practical application.

[0055] To verify the experimental reconstruction effect of a dual-line joint solution combustion flow field tomography reconstruction method with hybrid regularization proposed by the present invention, thermocouple measurements were carried out. The temperature distribution along the radial direction ( X = 0 mm) at the same height above the burner was measured and compared with the experimental reconstruction results, as Figure 6 shown. The results show that the present invention effectively reconstructs the temperature in the central area of the combustion flame and accurately restores the thermal gradient boundary generated by heat transfer, and is basically consistent with the trend of the thermocouple measurement results.

[0056] Based on the above method, an embodiment of the present invention also provides a flow field tomography reconstruction system corresponding to the above method. The system includes an absorption coefficient joint solution module, a hybrid regularization module, a prior constraint module, and a solution calculation module; The absorption coefficient joint solution module is used for: selecting two absorption lines, jointly solving the absorption coefficients of the two absorption lines, establishing a dual-line joint solution equation and combining it into a single optimization equation; The hybrid regularization module is used for: introducing hybrid regularization constraints into the single optimization equation to establish a hybrid regularization dual-line joint solution calculation mathematical model; The prior constraint module is used for: based on the hybrid regularization dual-line joint solution calculation mathematical model, setting a non-negative criterion for the absorption coefficient and introducing the temperature prior information of the flow field to obtain a hybrid regularization solution mathematical model with temperature boundary prior constraints; The solution calculation module is used for: solving the hybrid regularization solution mathematical model with temperature boundary prior constraints to obtain the absorption coefficient, and calculating the temperature distribution of the flow field using the absorption coefficient.

[0057] Based on the same inventive concept disclosed above, correspondingly, the present invention also provides an electronic device. As Figure 7 shown, the electronic device according to an embodiment of the present invention includes at least one processor and at least one memory that are electrically connected. The memory is electrically connected to the processor. Among them, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described above.

[0058] It should be noted that the electrical connection between the above-mentioned various units does not necessarily mean the connection between the lines. An indirect connection method can be applied to the embodiments of the present invention as long as the purpose of the present invention is achieved.

[0059] Based on the same inventive concept, the present invention also provides a computer storage medium. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0060] Based on the same inventive concept, the present invention also provides a computer program product, which is stored in at least one storage medium; the computer program product includes a number of instructions for causing at least one computer device to execute the method as described above.

[0061] Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for tomographic reconstruction of a flow field, characterized in that, the method includes, selecting two absorption lines, jointly solving the absorption coefficients of the two absorption lines, establishing a dual-line joint solution equation and combining it into a single optimization equation; introducing a mixed regularization constraint into the single optimization equation to establish a computational mathematical model for dual-line joint solution with mixed regularization; based on the computational mathematical model for dual-line joint solution with mixed regularization, setting a non-negativity criterion for the absorption coefficient and introducing the prior information of the temperature of the flow field to obtain a mixed regularization solution mathematical model with prior constraints on temperature bounds; solving the mixed regularization solution mathematical model with prior constraints on temperature bounds to obtain the absorption coefficient, and calculating the temperature distribution of the flow field using the absorption coefficient.

2. The method according to claim 1, characterized in that, the two absorption lines are the absorption lines of water molecules in the flow field to be measured.

3. The method according to claim 2, characterized in that, The two absorption lines are the absorption spectral lines with the center frequencies of the near-infrared band of water molecules being 7185.597 cm -1 and 7444.352 cm -1 respectively.

4. The method according to claim 1, characterized in that, the mixed regularization is to mix the Tikhonov Regularization and TV Regularization regularization methods.

5. The method according to claim 1, characterized in that, for the computational mathematical model for dual-line joint solution with mixed regularization, an empirical regularization weight parameter is selected to balance the importance of each sample.

6. The method according to claim 1, characterized in that, the computational mathematical model for dual-line joint solution with mixed regularization includes three parts: the first part is the calculation of the fidelity term, the second part is the mixed regularization term for each absorption line, and the third part is the mixed regularization term for the absorption coefficient ratio distribution.

7. The method according to claim 1, characterized in that, calculating the temperature distribution of the flow field using the absorption coefficient includes: discretizing the target reconstruction region into multiple grid cells and considering the thermophysical parameters within each grid cell as uniformly distributed; calculating the temperature value of each grid cell according to the ratio of the absorption coefficients of the two absorption lines; combining the temperature values of all grid cells to obtain the temperature distribution of the flow field.

8. A system for tomographic reconstruction of a flow field, characterized in that, the system includes an absorption coefficient joint solution module, a mixed regularization module, a prior constraint module, and a solution calculation module; the absorption coefficient joint solution module is used for: selecting two absorption lines, jointly solving the absorption coefficients of the two absorption lines, establishing a dual-line joint solution equation and combining it into a single optimization equation; the mixed regularization module is used for: introducing a mixed regularization constraint into the single optimization equation to establish a computational mathematical model for dual-line joint solution with mixed regularization; the prior constraint module is used for: based on the computational mathematical model for dual-line joint solution with mixed regularization, setting a non-negativity criterion for the absorption coefficient and introducing the prior information of the temperature of the flow field to obtain a mixed regularization solution mathematical model with prior constraints on temperature bounds; the solution calculation module is used for: solving the mixed regularization solution mathematical model with prior constraints on temperature bounds to obtain the absorption coefficient, and calculating the temperature distribution of the flow field using the absorption coefficient.

9. The system according to claim 8, wherein the two absorption lines are the absorption lines of water molecules in the flow field to be measured.

10. The system according to claim 9, wherein The two absorption lines are the absorption spectral lines with the central frequencies of the near-infrared band of water molecules being 7185.597 cm -1 and 7444.352 cm -1 respectively.

11. The system according to claim 8, wherein the hybrid regularization is to hybridly use the Tikhonov Regularization and TV Regularization methods.

12. The system according to claim 8, wherein the dual-line joint solution calculation mathematical model of hybrid regularization selects empirical regularization weight parameters to balance the importance of each sample.

13. The system according to claim 8, wherein the dual-line joint solution calculation mathematical model of hybrid regularization includes three parts: the first part is the calculation fidelity term, the second part is the hybrid regularization term for each absorption line, and the third part is the hybrid regularization term for the absorption coefficient ratio distribution.

14. The system according to claim 8, wherein calculating the temperature distribution of the flow field using the absorption coefficient includes: discretizing the target reconstruction region into multiple grid cells and regarding the thermophysical parameters within each grid cell as uniformly distributed; calculating the temperature value of each grid cell according to the ratio of the absorption coefficients of the two absorption lines; combining the temperature values of all grid cells to obtain the temperature distribution of the flow field.

15. An electronic device, characterized in that, comprising at least one processor and at least one memory that are electrically connected; the memory is electrically connected to the processor, wherein the memory stores instructions executable by at least one of the processors, and the instructions are executed by at least one of the processors so that at least one of the processors can execute the flow field tomography reconstruction method according to any one of claims 1-7.

16. A computer storage medium, wherein the computer-readable storage medium stores a computer program; the computer program, when executed by a processor, implements the flow field tomography reconstruction method according to any one of claims 1-7.

17. A computer program product, wherein the computer program product is stored in at least one storage medium; the computer program product includes several instructions for causing at least one electronic device to execute the flow field tomography reconstruction method according to any one of claims 1-7.

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